Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool

Objective: To explore the use of the Risk Assessment and Predictor Tool (RAPT) as a pre-operative tool to predict postoperative discharge destination and length of stay for patients undergoing total knee replacement (TKR) in Singapore. Participants and setting: A cohort of 569 patients undergoing pr...

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Main Authors: Tan, C., Loo, G., Pua, Y., Chong, H., Yeo, W., Ong, P., Lo, N., Allison, Garry
Format: Journal Article
Published: Elsevier Ltd 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/5531
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author Tan, C.
Loo, G.
Pua, Y.
Chong, H.
Yeo, W.
Ong, P.
Lo, N.
Allison, Garry
author_facet Tan, C.
Loo, G.
Pua, Y.
Chong, H.
Yeo, W.
Ong, P.
Lo, N.
Allison, Garry
author_sort Tan, C.
building Curtin Institutional Repository
collection Online Access
description Objective: To explore the use of the Risk Assessment and Predictor Tool (RAPT) as a pre-operative tool to predict postoperative discharge destination and length of stay for patients undergoing total knee replacement (TKR) in Singapore. Participants and setting: A cohort of 569 patients undergoing primary TKR at the Singapore General Hospital were recruited prospectively from November 2009 to June 2010. Intervention: All patients completed a modified RAPT questionnaire pre-operatively, and underwent standard clinical pathway guidelines for TKR throughout the study. Main outcome measures: Actual discharge destination (ADDest) and length of stay (LOS). Design: Total RAPT score and preferred discharge destination (PDD) were recorded pre-operatively, while ADDest and LOS were obtained immediately after discharge. Multivariable logistic regression and multivariable regression analysis were used to determine whether the RAPT items and score could predict the discharge outcomes. Results: Total RAPT score was a significant predictor of LOS for patients following TKR (R = 0.24, P < 0.001); the higher the RAPT score, the longer the LOS. Total RAPT score was also a significant predictor of actual discharge to home [odds ratio (OR) 2.32, 95% confidence interval (CI) 1.11 to 4.85]. PDD was a significant predictor for LOS (R = 0.22, P < 0.001) and ADDest (R = 0.33, P < 0.001). Patients who chose to be discharged home were more likely to be directly discharged home (OR 9.79, 95% CI 5.07 to 18.89, P < 0.001). Conclusion: Total RAPT score and PDD were significant predictors of ADDest and LOS for patients following TKR in Singapore. The ability to predict discharge outcomes following TKR could assist caregivers, healthcare professionals and administrators in optimising care and resource allocations for patients.
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spelling curtin-20.500.11937-55312017-09-13T14:42:15Z Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool Tan, C. Loo, G. Pua, Y. Chong, H. Yeo, W. Ong, P. Lo, N. Allison, Garry Total knee replacement Length of stay Risk Assessment and Predictor Tool Knee Objective: To explore the use of the Risk Assessment and Predictor Tool (RAPT) as a pre-operative tool to predict postoperative discharge destination and length of stay for patients undergoing total knee replacement (TKR) in Singapore. Participants and setting: A cohort of 569 patients undergoing primary TKR at the Singapore General Hospital were recruited prospectively from November 2009 to June 2010. Intervention: All patients completed a modified RAPT questionnaire pre-operatively, and underwent standard clinical pathway guidelines for TKR throughout the study. Main outcome measures: Actual discharge destination (ADDest) and length of stay (LOS). Design: Total RAPT score and preferred discharge destination (PDD) were recorded pre-operatively, while ADDest and LOS were obtained immediately after discharge. Multivariable logistic regression and multivariable regression analysis were used to determine whether the RAPT items and score could predict the discharge outcomes. Results: Total RAPT score was a significant predictor of LOS for patients following TKR (R = 0.24, P < 0.001); the higher the RAPT score, the longer the LOS. Total RAPT score was also a significant predictor of actual discharge to home [odds ratio (OR) 2.32, 95% confidence interval (CI) 1.11 to 4.85]. PDD was a significant predictor for LOS (R = 0.22, P < 0.001) and ADDest (R = 0.33, P < 0.001). Patients who chose to be discharged home were more likely to be directly discharged home (OR 9.79, 95% CI 5.07 to 18.89, P < 0.001). Conclusion: Total RAPT score and PDD were significant predictors of ADDest and LOS for patients following TKR in Singapore. The ability to predict discharge outcomes following TKR could assist caregivers, healthcare professionals and administrators in optimising care and resource allocations for patients. 2014 Journal Article http://hdl.handle.net/20.500.11937/5531 10.1016/j.physio.2013.02.003 Elsevier Ltd restricted
spellingShingle Total knee replacement
Length of stay
Risk Assessment and Predictor Tool
Knee
Tan, C.
Loo, G.
Pua, Y.
Chong, H.
Yeo, W.
Ong, P.
Lo, N.
Allison, Garry
Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title_full Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title_fullStr Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title_full_unstemmed Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title_short Predicting discharge outcomes after total knee replacement using the Risk Assessment and Predictor Tool
title_sort predicting discharge outcomes after total knee replacement using the risk assessment and predictor tool
topic Total knee replacement
Length of stay
Risk Assessment and Predictor Tool
Knee
url http://hdl.handle.net/20.500.11937/5531